OpenCV计算外包矩形

分别计算平行于坐标轴的外接矩形和面积最小的外接矩形

#include <opencv.hpp>
#include <iostream>
using namespace std;
void CornerSift(string ImageName,cv::Rect &boundingRec,cv::RotatedRect &minAreaRec)
{
    
	cv::Mat ImageInput;
	ImageInput = cv::imread(ImageName,cv::ImreadModes::IMREAD_COLOR);
	if (ImageInput.empty())
	{
    
		cout << "图像文件为空！" << std::endl;
		return;
	}
	cv::Mat ImageRGB/*角点检测彩色*/, ImageGray;
	ImageInput.copyTo(ImageRGB);
	cvtColor(ImageRGB, ImageGray, cv::COLOR_BGR2GRAY);
	vector<cv::KeyPoint> Keypoints;
	float thContrast = 0.03;//角点对比度阈值
	float thEdge = 10;//特征值之比。越小角点质量越高
	cv::Ptr<cv::Feature2D> f2d = cv::SIFT::create(0, 3, thContrast, thEdge, 1.6);
	f2d->detect(ImageGray, Keypoints);
	int num = Keypoints.size();
	//打印点坐标
	vector<cv::Point2f> kPxys;
	for (int i = 0; i < num; i++)
	{
    
		cv::KeyPoint kP = Keypoints[i];
		//cout << kP.pt.x << "\t" << kP.pt.y << endl;
		kPxys.push_back(kP.pt);
	}
	//绘制特征点
	cv::drawKeypoints(ImageRGB, Keypoints, ImageRGB, cv::Scalar(255, 255, 0), cv::DrawMatchesFlags::DEFAULT);
	//基于sift特征点计算最小外接矩形
	//平行坐标轴的外接矩形
	boundingRec = cv::boundingRect(kPxys);
	cv::rectangle(ImageRGB, boundingRec, cv::Scalar(255, 0, 0),2);
	//面积最小外接矩形
	minAreaRec = cv::minAreaRect(kPxys);
	cv::Point2f minAreaRecOPoints[4];
	minAreaRec.points(minAreaRecOPoints);
	for (int i = 0; i < 4; i++)
	{
    
		cv::Point2f startPoint = minAreaRecOPoints[i];
		cv::Point2f endPoint;
		if (i != 3)
		{
    
			endPoint = minAreaRecOPoints[i + 1];
		}
		else
		{
    
			endPoint = minAreaRecOPoints[0];
		}
		cv::line(ImageRGB, startPoint, endPoint, cv::Scalar(0, 255, 0), 2);
	}
	cv::imshow("2D Features", ImageRGB);
	cv::waitKey(0);
	cv::destroyAllWindows();
	return;
}

int main()
{
    
	cv::Rect boundingRec;
	cv::RotatedRect minAreaRec;
	CornerSift("t3.jpg",boundingRec,minAreaRec);
	//获取矩形相关信息
	cv::Point2f center = minAreaRec.center;
	cv::Size2f recSize = minAreaRec.size;
	float recAngle = minAreaRec.angle;
	cout << center << endl;
	cout << recSize << endl;
	cout << recAngle << endl;
	return 0;
}

效果